Data Engineer

The Data Engineer will be responsible for building and maintaining our data infrastructure to support reporting, analytics, and data science initiatives. The ideal candidate will have strong skills in data architecture, ETL, SQL, and Python within a Git-managed environment, as well as a proven ability to collaborate with both business stakeholders and data team colleagues to deliver robust, scalable data frameworks. This individual will possess strong operational skills to drive efficiency and speed, expertise in building repeatable data engineering processes, strong project management abilities, and a forward-looking vision for delivering impactful data products.

Responsibilities

• Create and orchestrate data pipelines within a state-of-the-art AWS environment (Redshift, EC2, EMR, S3, Lambda, Glue, etc.).
• Manage all aspects of the data and analytics ecosystem—from ingestion to ETL to aggregate tables—to meet analytics and reporting needs.
• Design and implement internal data pipeline processes and improvements using modern techniques such as automation, optimization, and infrastructure redesign for scalability.
• Develop scripts for scheduling data ingestion and synchronization, and implement backend logic to create data marts based on business requirements for stakeholder self-service.
• Partner with data architects to build frameworks for defining metrics as code and optimizing data search and retrieval.
• Troubleshoot production data jobs and processes to resolve data quality issues and improve pipeline performance.
• Build and assemble large, complex data sets with multi-dimensional relationships to meet functional and non-functional business requirements.
• Develop integrations between systems to ensure seamless data flow.

Qualifications

• Bachelor’s degree or higher in a quantitative or technical field (e.g., Computer Science, Statistics, Engineering) or equivalent experience.
• 5+ years of experience in data engineering, database engineering, business intelligence, or business analytics.
• 5+ years of SQL experience for reporting and transformation (Redshift, MySQL, PostgreSQL, Snowflake, Databricks).
• 4+ years of Python experience, including class development, within a Git-managed CI/CD team development environment.
• 4+ years of experience with schema design and dimensional data modeling.
• Strong interest in understanding business strategy, not just data architecture, and a focus on how data engineering contributes to organizational goals.
• Experience with Data Lake architectures and integrating structured and unstructured data into unified models.
• Ability to define and align to a long-term vision, with a focus on reliability, curiosity, and self-sufficiency in diagnosing issues by digging into code, data, and logs.
• Experience with API design and development of RESTful web services.
• Analytical mindset with the ability to structure and process qualitative data and draw insightful conclusions.
• Experience with data science and machine learning (a plus).
• Experience with GIS (a plus).
• Data visualization experience with tools such as Tableau (a plus).
• Experience with JIRA (preferred).

Job Types: Full-time, Permanent

Experience:

• data engineering (sql and python): 5 years (Required)
• schema design and dimensional data modeling: 4 years (Required)
• Create and orchestrate data pipelines with AWS: 3 years (Required)

Work Location: In person